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Birmingham, AL, United States

Hsiao P.Y.,Pennsylvania State University | Mitchell D.C.,Pennsylvania State University | Coffman D.L.,Pennsylvania State University | Allman R.M.,Birmingham Atlanta VA Geriatric Research | And 9 more authors.
Journal of Nutrition, Health and Aging | Year: 2013

Objectives: To characterize dietary patterns among a diverse sample of older adults (≥ 65 years). Design: Cross-sectional. Setting: Five counties in west central Alabama. Participants: Community-dwelling Medicare beneficiaries (N=416; 76.8 ±5.2 years, 56% female, 39% African American) in the University of Alabama at Birmingham (UAB) Study of Aging. Measurements: Dietary data collected via three, unannounced 24-hour dietary recalls was used to identify dietary patterns. Foods were aggregated into 13 groups. Finite mixture modeling (FMM) was used to classify individuals into three dietary patterns. Differences across dietary patterns for nutrient intakes, sociodemographic, and anthropometric measurements were examined using chi-square and general linear models. Results: Three dietary patterns were derived. A "More healthful" dietary pattern, with relatively higher intakes of fruit, vegetables, whole grains, eggs, nuts, legumes and dairy, was associated with lower energy density, higher quality diets as determined by Healthy Eating Index (HEI)-2005 scores and higher intakes of fiber, folate, vitamins C and B6, calcium, iron, magnesium, and zinc. The "Westernlike" pattern was defined by an intake of starchy vegetables, refined grains, meats, fried poultry and fish, oils and fats and was associated with lower HEI-2005 scores. The "Low produce, high sweets" pattern was characterized by high saturated fat, and low dietary fiber and vitamin C intakes. The strongest predictors of better diet quality were female gender and non-Hispanic white race. Conclusion: The dietary patterns identified may provide a useful basis on which to base dietary interventions targeted at older adults. Examination of nutrient intakes regardless of the dietary pattern suggests that older adults are not meeting nutrient recommendations and should continue to be encouraged to choose high quality diets. © 2013 Serdi and Springer Verlag France. Source


Robertson H.T.,University of Alabama at Birmingham | Smith D.L.,Nutrition Obesity Research Center | Smith D.L.,University of Alabama at Birmingham | Pajewski N.M.,University of Alabama at Birmingham | And 6 more authors.
Journals of Gerontology - Series A Biological Sciences and Medical Sciences | Year: 2011

Many rodent experiments have assessed effects of diets, drugs, genes, and other factors on life span. A challenge with such experiments is their long duration, typically over 3.5 years given rodent life spans, thus requiring significant time costs until answers are obtained. We collected longevity data from 15 rodent studies and artificially truncated them at 2 years to assess the extent to which one will obtain the same answer regarding mortality effects. When truncated, the point estimates were not significantly different in any study, implying that in most cases, truncated studies yield similar estimates. The median ratio of variances of coefficients for truncated to full-length studies was 3.4, implying that truncated studies with roughly 3.4 times as many rodents will often have equivalent or greater power. Cost calculations suggest that shorter studies will be more expensive but perhaps not so much to not be worth the reduced time. © The Author 2010. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. Source


News Article | January 11, 2016
Site: http://boingboing.net

Why all scientific diet research turns out to be bullshit The gold standard for researching the effects of diet on health is the self-reported food-diary, which is prone to lots of error, underreporting of "bad" food, and changes in diet that result from simply keeping track of what you're eating. The standard tool for correcting these errors comparisons with more self-reported tests. As if that wasn't bad enough, eating correlates with everything, so if you go "p-hacking" through the data, looking for correlations after the fact. My take on all this is that if there was a gross, easily observable effect from eating food that humans have been eating for hundreds or thousands of years, we'd already know about it. That's why the amazing study showing that kiwi fruit promote good sleep turns out to have only 24 subjects, only two of them men, to rely on self-reporting, and to be funded by the kiwi industry. That's why the incredible news that tomatoes improve memory turns out to be a preliminary result of a small study on very old Japanese people. If you're not very old and of Japanese descent, that finding means something between nothing and so little as to be indistinguishable from nothing. So a good rule of thumb, as far as I'm concerned, is that any nutrition study that finds any genuinely surprising, large-scale effect, is bullshit. Tiny, difficult-to-disentangle effects? Sure, there's probably a lot of those. But "Eating peanuts makes you grow extra nipples on your ass-cheeks?" If that were the case, we'd have noticed by now. Although concerns about self-reported dietary intakes have been around for decades, the debate has come to a head in recent years, said David Allison, director of the University of Alabama’s Nutrition Obesity Research Center in Birmingham. Allison was an author of a 2014 expert report from the Energy Balance Measurement Working Group that called it “unacceptable” to use “decidedly inaccurate” methods of measurement to set health care policies, research and clinical practice. “In this case,” the researchers wrote, “the adage ‘something is better than nothing’ must be changed to ‘something is worse than nothing.’” The problems with food questionnaires go even deeper. They aren’t just unreliable, they also produce huge data sets with many, many variables. The resulting cornucopia of possible variable combinations makes it easy to p-hack your way to sexy (and false) results, as we learned when we invited readers to take an FFQ and answer a few other questions about themselves. We ended up with 54 complete responses and then looked for associations — much as researchers look for links between foods and dreaded diseases. It was silly easy to find them. You Can’t Trust What You Read About Nutrition [Christie Aschwanden/538]


Locher J.L.,University of Alabama at Birmingham | Locher J.L.,Center for Aging | Locher J.L.,Lister Hill Center for Health Policy | Locher J.L.,Nutrition Obesity Research Center | And 15 more authors.
Journal of Nutrition in Gerontology and Geriatrics | Year: 2011

We conducted a study designed to evaluate the efficacy and feasibility of a multilevel self-management intervention to improve nutritional intake in a group of older adults receiving Medicare home health services who were at especially high risk for experiencing undernutrition. The Behavioral Nutrition Intervention for Community Elders (B-NICE) trial used a prospective randomized controlled design to determine whether individually tailored counseling focused on social and behavioral aspects of eating resulted in increased caloric intake and improved nutrition-related health outcomes in a high-risk population of older adults. The study was guided by the theoretical approaches of the Ecological Model and Social Cognitive Theory. The development and implementation of the B-NICE protocol, including the theoretical framework, methodology, specific elements of the behavioral intervention, and assurances of the treatment fidelity, as well as the health policy implications of the trial results, are presented in this article. © 2011 Copyright Taylor and Francis Group, LLC. Source


Dhurandhar E.J.,University of Alabama at Birmingham | Dawson J.,Nutrition Obesity Research Center | Alcorn A.,Nutrition Obesity Research Center | Larsen L.H.,Copenhagen University | And 9 more authors.
American Journal of Clinical Nutrition | Year: 2014

Background: Breakfast is associated with lower body weight in observational studies. Public health authorities commonly recommend breakfast consumption to reduce obesity, but the effectiveness of adopting these recommendations for reducing body weight is unknown. Objective: We tested the relative effectiveness of a recommendation to eat or skip breakfast on weight loss in adults trying to lose weight in a free-living setting. Design: We conducted a multisite, 16-wk, 3-parallel-arm randomized controlled trial in otherwise healthy overweight and obese adults [body mass index (in kg/m2) between 25 and 40] aged 20-65 y. Our primary outcome was weight change. We compared weight change in a control group with weight loss in experimental groups told to eat breakfast or to skip breakfast [no breakfast (NB)]. Randomization was stratified by prerandomization breakfast eating habits. A total of 309 participants were randomly assigned. Results: A total of 283 of the 309 participants who were randomly assigned completed the intervention. Treatment assignment did not have a significant effect on weight loss, and there was no interaction between initial breakfast eating status and treatment. Among skippers, mean (±SD) baseline weight-, age-, sex-, site-, and race-adjusted weight changes were -0.71± 1.16, -0.76 ± 1.26, and -0.61 ± 1.18 kg for the control, breakfast, and NB groups, respectively. Among breakfast consumers, mean (±SD) baseline weight-, age-, sex-, site-, and race-adjusted weight changes were -0.53 ± 1.16, -0.59 ± 1.06, and -0.71 ± 1.17 kg for the control, breakfast, and NB groups, respectively. Self-reported compliance with the recommendation was 93.6% for the breakfast group and 92.4% for the NB group. Conclusions: A recommendation to eat or skip breakfast for weight loss was effective at changing self-reported breakfast eating habits, but contrary to widely espoused views this had no discernable effect on weight loss in free-living adults who were attempting to lose weight. This trial was registered at clinicaltrails.gov as NCT01781780. © 2014 American Society for Nutrition. Source

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